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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- Korean Institute of Information Scientists and Engineers Journal of Electrical Engineering and Information Science Journal of Electrical Engineering and Information Science Vol.4 No.2
- 발행연도
- 1999.4
- 수록면
- 224 - 231 (8page)
이용수
초록· 키워드
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This paper presents a new distributed processing approach to "direct" blind equalization of Single Input Multiple Output (SIMO) channels. Under mild conditions, it is shown here that we can recover the original source signal up to its scaled and delayed version by decorrelating the equalizer (neural network) outputs in spatio-temporal domain. "Spatio-temporal anti-Hebbian" learning rule (simple, local, biologically plausible) is derived from an information-theoretic approach and is applied for spatio-temporal decorrelation task. A linear feedback neural network with FIR synapses is proposed and is shown to be a good candidate for the equalizer. Computer simulation experiments confirm the validity and high performance of the proposed neural network with the associated learning algorithm.
목차
Abstract
Ⅰ. Introduction
Ⅱ. Existence of the Inverse
Ⅲ. A New Equalization Criterion
Ⅳ. Neural Network Model and Learning Algorithm
Ⅴ. Computer Simulations
Ⅵ. Conclusions
Appendix
Acknowledgements
References
저자소개
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